1. Field of the Invention
The present invention relates to a character recognition device, and in particular to a character recognition device which inputs an image of a series of characters and outputs the results of recognition of individual characters.
2. Description of the Related Art
When recognizing words given as an image, conventionally, for example, as in Japanese Patent Application, First Publication, No. Hei 6-348911, the word image is converted into two colors, the circumscribing rectangle which circumscribes the black pixel concatenated component is found, these circumscribing rectangles are integrated based on the graphical characteristics such as the distances between the surrounding circumscribing rectangles, the integrated rectangular areas are subject to character recognition, the character recognition result is checked against correct word spellings stored in a dictionary, and as a result the character with the largest degree of agreement is output.
A problem in the above-described conventional technology is that when there is a character with a part missing in the image, it cannot be correctly read. The reason is that when the rectangular area is subject to character recognition, it is assumed that its circumscribing rectangle matches a character frame of a character in the character recognition dictionary. This assumption does not hold when a part of the character is missing, and there is the concern that the result of the character recognition of this character will be obviously lacking validity.
For example, assume that an image including the character `Y` is extracted as shown in FIG. 15A. FIG. 15A is the case that one part of the right side of `Y` is missing. In contrast, assume that the template for the `Y` character type as shown in FIG. 15C is provided in the character recognition dictionary.
Generally, the character recognition device calculates the degree of similarity from the match between the circumscribing rectangle in the recognition object image and the character frame of the template in the character recognition dictionary. For example, the degree of similarity is calculated with FIG. 15C after FIG. 15A is transformed into FIG. 15B in order to match the character frame of the template. Because the degree of similarity between FIG. 15B after transformation and the template shown in FIG. 15C is low, this causes a recognition error.
That is, if an extracted character has a missing part, there is the problem that a correct character recognition result will not be obtained because the similarity with the template of the correct character type is low, or because of the possibility that by chance there may be a high degree of similarity with the template of a character type other than the correct one.